What We Expect From Authors

JMR expects a data availability statement in every manuscript. Authors should describe where data, code, and materials are stored and how they can be accessed.

• Provide a repository link or accession number whenever possible.
• Specify access conditions for sensitive or restricted data.
• List software and versions used for analysis.
• Include documentation and variable definitions for reuse.

We encourage authors to align data practices with FAIR principles: data should be findable, accessible, interoperable, and reusable. Clear data documentation increases reviewer confidence and accelerates reuse by other mammal researchers.

Recommended Archiving Options

If a repository supports versioning, keep your archived dataset aligned with the final accepted manuscript. Include the DOI or persistent link in your data availability statement.

Human Data And Confidentiality

Mammal research often involves human participants and sensitive data. Authors must follow ethical standards and legal requirements for data protection.

• De identify participant data before sharing.
• Remove direct identifiers and consider re identification risks.
• Use controlled access repositories for sensitive datasets.
• Describe consent language related to data sharing.

For telemetry, behavioral, or wildlife health datasets, consider the risk of indirect identification of sensitive locations or species. Provide aggregated outputs when full datasets cannot be released, and include a description of the steps taken to protect sensitive information.

Embargoes And Release Schedules

Some datasets may require an embargo period due to ongoing analyses, participant agreements, or sponsor requirements. JMR allows reasonable embargoes when they are clearly stated and time limited.

• Include the expected release date in the data availability statement.
• Explain the rationale for any embargo and who approves it.
• Provide a contact method for qualified access during the embargo.

Reproducibility For Computational Work

For modeling, imaging, and machine learning studies, JMR encourages sharing code and analysis pipelines to improve reproducibility.

• Include scripts, notebooks, or pipelines used for analysis.
• Describe dependencies, software versions, and operating systems.
• Provide a README that explains how to reproduce results.
• Indicate any proprietary tools or restrictions.

If your analysis relies on large computing resources, include a brief description of hardware requirements and estimated runtime to help readers evaluate reproducibility.

Third Party Tools And Licensed Instruments

If your study uses proprietary tests, copyrighted instruments, or licensed software, confirm that you have permission to archive or share materials. When sharing is not allowed, provide a description of how readers can obtain access from the rights holder.

Data Licensing And Reuse

Use clear licensing for datasets and code so that other researchers understand how they can reuse the materials. Open licenses are encouraged when appropriate.

Meeting Sponsor Requirements

Many funders require data sharing plans and open access availability. JMR supports compliance by allowing repository links, embargo timelines, and clear statements of access conditions.

• Confirm funder requirements before submission.
• Include grant numbers in the funding statement.
• Ensure the data plan matches the consent language.

Need Guidance On Data Sharing?

If you are unsure about appropriate repositories or access controls, contact the editorial office for guidance. We can help align your data plan with ethical standards and funder requirements. Early questions prevent delays during editorial screening.